Fine Dnc Co Beneish M-Score Historical Data
The historical data trend for Fine Dnc Co's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
Fine Dnc Co Beneish M-Score Chart
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Fine Dnc Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.58 |
-2.91 |
-4.07 |
-6.69 |
-3.73 |
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Fine Dnc Co Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-5.38 |
4.92 |
-1.54 |
-3.73 |
-2.35 |
Competitive Comparison of Fine Dnc Co's Beneish M-Score
For the Electronic Components subindustry, Fine Dnc Co's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Fine Dnc Co's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, Fine Dnc Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Fine Dnc Co's Beneish M-Score falls into.
Fine Dnc Co Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of Fine Dnc Co for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 1.6194 | + | 0.528 * 0.9639 | + | 0.404 * 0.8699 | + | 0.892 * 0.9703 | + | 0.115 * 2.0033 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0467 | + | 4.679 * -0.101666 | - | 0.327 * 0.9123 |
| = | -2.35 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was ₩10,466 Mil.
Revenue was 16056.107 + 16890.581 + 8482.919 + 9699.656 = ₩51,129 Mil.
Gross Profit was 2797.231 + 391.505 + -536.75 + -729.275 = ₩1,923 Mil.
Total Current Assets was ₩22,170 Mil.
Total Assets was ₩112,553 Mil.
Property, Plant and Equipment(Net PPE) was ₩31,825 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩2,326 Mil.
Selling, General, & Admin. Expense(SGA) was ₩2,451 Mil.
Total Current Liabilities was ₩55,694 Mil.
Long-Term Debt & Capital Lease Obligation was ₩4,589 Mil.
Net Income was 658.654 + -461.073 + -2021.426 + -7794.716 = ₩-9,619 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -1304.765 + 6319.762 + -5218.886 + 2028.098 = ₩1,824 Mil.
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Total Receivables was ₩6,661 Mil.
Revenue was 8410.666 + 16791.912 + 10346.4 + 17144.213 = ₩52,693 Mil.
Gross Profit was -15.365 + 912.136 + -338.079 + 1351.271 = ₩1,910 Mil.
Total Current Assets was ₩29,672 Mil.
Total Assets was ₩115,894 Mil.
Property, Plant and Equipment(Net PPE) was ₩16,909 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩2,672 Mil.
Selling, General, & Admin. Expense(SGA) was ₩2,414 Mil.
Total Current Liabilities was ₩59,363 Mil.
Long-Term Debt & Capital Lease Obligation was ₩8,676 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (10465.912 / 51129.263) | / | (6660.702 / 52693.191) |
| = | 0.204695 | / | 0.126405 |
| | = | 1.6194 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (1909.963 / 52693.191) | / | (1922.711 / 51129.263) |
| = | 0.036247 | / | 0.037605 |
| | = | 0.9639 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (22169.589 + 31825.498) / 112552.792) | / | (1 - (29671.923 + 16909.155) / 115894.237) |
| = | 0.520269 | / | 0.598073 |
| | = | 0.8699 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 51129.263 | / | 52693.191 |
| | = | 0.9703 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (2671.649 / (2671.649 + 16909.155)) | / | (2326.073 / (2326.073 + 31825.498)) |
| = | 0.136442 | / | 0.06811 |
| | = | 2.0033 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (2451.493 / 51129.263) | / | (2413.782 / 52693.191) |
| = | 0.047947 | / | 0.045808 |
| | = | 1.0467 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((4588.707 + 55693.975) / 112552.792) | / | ((8676.224 + 59363.452) / 115894.237) |
| = | 0.535595 | / | 0.587084 |
| | = | 0.9123 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (-9618.561 - 0 | - | 1824.209) | / | 112552.792 |
| | = | -0.101666 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
Fine Dnc Co has a M-score of -2.35 suggests that the company is unlikely to be a manipulator.
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